container-host-aiops
Container Host AIops
Disclaimer: Community-maintained open-source project. Not affiliated with, endorsed by, or sponsored by Docker, Inc., Portainer.io, or any container-platform vendor. "Docker", "Portainer" and all product/trademark names belong to their respective owners. MIT licensed.
Governed AI-ops for non-orchestrator container hosts — the Docker Engine API (over a local unix socket or a TCP host), Portainer (its management API, which also proxies Docker), and Podman (a rootful/rootless service socket speaking the Docker-compatible API plus libpod-native endpoints) — with a built-in governance harness: a unified audit log over both MCP and CLI, a runaway/budget safety guard, and undo-token recording. It records every operation; it does not decide whether a write is permitted — that is the agent's or the account's call. Multi-platform by construction: a registry keyed by platform means a per-target platform field (docker / portainer / podman) selects the API shape, and another host family could be added later without touching the ops/CLI/MCP layers. Exercised against a live Docker Engine 27.5.1 daemon (doctor, overview, the three flagship analyses, and a governed stop_container with audit + undo recorded); the Portainer and Podman API paths are covered by the mock suite only.
What it does
Three flagship signature analyses, plus the guarded reads and writes around them:
Restart-loop RCA — inspect containers for restart count + exit code, flag the crash-looping ones (restartCount over threshold, or restarting/dead, or a non-zero exit), and map each to a likely cause + action from the exit code (137 OOM/SIGKILL, 143 SIGTERM, 139 segfault, 127 bad entrypoint, …), with a tail of logs. Every ranking carries its numbers, not a black-box verdict.
Resource-pressure analysis — a one-shot CPU%/memory% sample per running container vs its configured limits, flagging each "near" (≥ 80% of a threshold) or "over", with a recommendation (raise a limit, set a missing memory limit, scale out).
Image & volume bloat — dangling images + dangling volumes + build cache from
system/df, totalled into prune candidates with reclaimable bytes.
What works
CLI (
container-host-aiops ...):init,overview,container,image,volume,network,system,stack,pod,analyze,manage,secret,doctor,mcp.MCP server (
container-host-aiops mcporcontainer-host-aiops-mcp): 38 tools (29 read, 9 write), every one wrapped with the bundled@governed_toolharness.Connection layer: Docker over a unix socket (
httpx.HTTPTransport(uds=...)) or a TCP host; Portainer over HTTPS with anX-API-Keytoken that also proxies the Docker API of a managed endpoint; Podman over its rootful/rootless service socket (autodetected:$XDG_RUNTIME_DIR/podman/podman.sockfirst, then/run/podman/podman.sock) speaking the Docker-compat layer (paths reused wholesale) plus libpod-native endpoints. A local Docker/Podman socket needs no secret — the socket's file permissions are the boundary.Encrypted credentials: the Portainer API token lives in an encrypted store
~/.container-host-aiops/secrets.enc(Fernet + scrypt) — never plaintext on disk. Unlock with a master password fromCONTAINER_HOST_AIOPS_MASTER_PASSWORD(MCP/CI) or an interactive prompt (CLI).Reversibility: mutating writes fetch the real before-state first and record a faithful inverse (
stop↔start;update_containerrestores prior CPU/memory limits). Irreversible ops (remove_container,prune_images,prune_volumes,recreate_stack) capture the before-state for audit but declare no undo.Safety: every state-changing CLI op supports
--dry-runand requires double confirmation; every write MCP tool takes adry_runpreview — and prune previews list what would be removed + reclaimable bytes before doing it.
What this tool does, and does not, decide
It delivers container-host operations — reads and writes — accurately and efficiently, and records every one of them. It does not decide whether a write is allowed to happen. That is the agent's judgement, or the permission of the account you connect it with: point it at a Docker socket mounted read-only, or a Portainer account without write scope, and the writes fail at the server — the place that actually owns the permission.
So there is no read-only switch, no policy file, no approval gate to configure.
The one thing the tool guarantees is that nothing is silent: every call, over
MCP and over the CLI alike, lands an audit row in
~/.container-host-aiops/audit.db, and destructive writes still capture their
before-state and record an inverse where one exists.
Each tool declares a
risk_level, kept in agreement with its[READ]/[WRITE]documentation tag by a test, and carried into the audit row as a descriptive tier — so a reviewer can see at a glance that a row was a high-risk delete. It is a label, not a gate.
Capability matrix (38 MCP tools)
Domain | Tools | Count | R/W |
Overview |
| 1 | read |
Containers |
| 6 | read |
Images |
| 4 | read |
Volumes |
| 3 | read |
Networks |
| 2 | read |
System |
| 4 | read |
Stacks |
| 4 | read |
Pods (Podman) |
| 1 | read |
Analyses (flagship) |
| 3 | read |
Writes |
| 4 | write (high) |
| 4 | write (medium) |
The three analyses accept injected data for offline analysis, or pull live from a configured target. list_endpoints/list_stacks/stack_detail require a portainer target; list_compose_stacks (Compose project rollup by the com.docker.compose.project label, with per-stack health) works on docker or podman; list_pods requires a podman target (Docker/Portainer have no pod concept).
Platform support matrix
Capability | docker | portainer | podman |
Container / image / volume / network / system reads | ✅ | ✅ (proxied) | ✅ (compat) |
Flagship analyses (restart-loop RCA, resource pressure, bloat) | ✅ | ✅ | ✅ (compat) |
Lifecycle + prune writes (stop/start/restart/remove/update/prune) | ✅ | ✅ | ✅ (compat) |
Compose-stack rollup ( | ✅ | ✅ (proxied) | ✅ |
Portainer endpoints / stacks / | — | ✅ | — |
Podman pods ( | — | — | ✅ |
Quick start
uv tool install container-host-aiops # or: pipx install container-host-aiops
container-host-aiops init # wizard: add a Docker/Podman socket or Portainer target
container-host-aiops doctor # verify config, secrets, connectivity
container-host-aiops overview # one-shot host health
container-host-aiops analyze restart-loop # crash-looping containers + cause/action
container-host-aiops container list --running # running containersRun as an MCP server (stdio):
export CONTAINER_HOST_AIOPS_MASTER_PASSWORD=... # only needed for Portainer targets
container-host-aiops-mcpGovernance
Every operation — MCP and CLI — passes through the bundled @governed_tool
harness. It records; it does not authorize (see above).
Audit — every call (params, result, status, duration, risk tier, and any operator-supplied approver/rationale) is logged to
~/.container-host-aiops/audit.db(relocatable viaCONTAINER_HOST_AIOPS_HOME). The CLI writes the same row the MCP path does — there is no unaudited entry point.Runaway guard — a safety backstop, not an authorization gate: the same call hammered in a tight loop trips a circuit breaker so a stuck agent can't burn unbounded calls/time. Disable with
CONTAINER_HOST_RUNAWAY_MAX=0; optional hard ceilings viaCONTAINER_HOST_MAX_TOOL_CALLS/CONTAINER_HOST_MAX_TOOL_SECONDS.Undo recording — reversible writes record an inverse descriptor built from the fetched before-state.
Risk tier — a descriptive label on the audit row derived from
risk_level; it gates nothing.
Scope
This is the container-host member of the AIops-tools family (governed AI-ops with audit + budget + undo), for single-host Docker / Portainer / Podman. It is deliberately NOT for a cluster orchestrator, a hypervisor, a storage appliance, a backup product, or OT / industrial edge — those are separate tools/lines.
Missing a capability?
Coverage is intentionally a curated subset of the Docker Engine + Portainer + Podman (libpod) APIs. Missing a call, or want another container host family? Open an issue or PR — contributions welcome.
Verification status
Docker — exercised against a live Docker Engine 27.5.1 daemon:
doctorandoverviewconnected over the local socket, therestart-loopand image/volumebloatanalyses were run against real crash-looping containers and real reclaimable data, and a governedstop_containerwrote a row to the audit DB and recorded a working undo descriptor.Portainer and Podman — mock-validated only. Those API paths are modelled from each project's public API shape and have not been exercised against a live server.
The full checklist — what the mock suite guarantees, what the Docker run already satisfied, and what a Portainer/Podman run still has to prove — is in docs/VERIFICATION.md.
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